3.1 Characterization of the soil from the locations
All the locations had evidence of glyphosate contamination though the contamination levels varied depending on location (Figure 1) and they were significant (p<0.05). Location 1 had the highest contamination comprising 319.1 mg/kg glyphosate and 194.2 mg/kg AMPA. Location 3 showed increased glyphosate level without transformation product (AMPA). This could suggest the active state of the organisms present. Among the locations, the lower level of glyphosate was observed more rapid in location 4 with only traces of glyphosate present (6.98 mg/kg).
Correspondingly, the fungal density varied within the location (Figure 2). There was high enumeration of fungal count in locations where AMPA concentration was high and with significant concentrations of glyphosate. However, other locations where AMPA concentration was low or absent had low fungal count. This implies active metabolic state of the fungi. As a result, this study evaluates the relationship between the fungal density, glyphosate and AMPA. The Pearson correlation shows that fungal load is significantly related to AMPA (r=0.94965; p≤0.05) in comparison to glyphosate.
3.2 Selection and isolation of glyphosate degraders
A total of 14 isolates were obtained from the farms (Table 1). The fungal inoculum from soils enrichment were plated on MSM agar plates to check for their ability to grow in the presence of glyphosate on solid media. It was observed that S1b, S1c, S2.3, S3.2, S3.3, S4.1 and S4.4 isolates did not grow from any of the enriched soils on MSM agar when glyphosate was added externally, during the set incubation time. They displayed poor (+) clear zone, therefore, no further analysis was conducted on them. The isolates that showed good (++) clear zone (S1a, S1d, S2.1, S3.1, S4.1 and S4.3) were further analyzed for their ability to degrade glyphosate. A total of six (6) potential degraders were obtained after successive sub-culturing from the soils (Table 2).
3.3 Enrichment of glyphosate degraders
We use optical density (OD) at a wavelength of 600nm (OD600) in addition to colony forming units (cfu) to evaluate microbial enrichment and growth in liquid fungal culture (figure 3). Several distinct growth phases were observed within the fungal growth curve, and these were the lag phase, the exponential or log phase, the stationary phase, and the death phase. Each of these phases represents a distinct period of growth that is associated with typical physiological changes in the cell culture.
Six fungal isolates were stimulated to grow in the presence of glyphosate. The glyphosate mixed with MSM showed enhanced growth of the fungal isolates as shown by their optical density and cfu. The logarithmic growth phase for OD600 lasted for 8 days in all the fungal isolates while for cfu, it lasted for 24 days. The stationary phase commenced after day 8 in growth curves for OD600 till end of the experiment whereas the cfu had a very sharp stationary phase 24 to day 28. The exponential growth (log phase) for cfu was observed to be biphasic with a transition from an initial to a subsequently slower rate of growth leading to the stationery phase. The first exponential phase was between 8 days and 12 days, while the second exponential phase was between 16 day and 24 days. The OD600 growth did not have death phase while cfu had a death phase after 28th day of incubation until the end the experiment. This discrepancy between OD600 and cfu could be from the hypothesis that optical density measurement is the quantity of viable and non-viable cells in a sample. The colony forming unit measures only the viable cells in a sample. An OD 600nm is an approximation CFU/ml and cannot fully take into account the non-viable cells the OD may be reading. It may also depends on the microorganism that is being researched.
Consequently, the specific growth rate estimated as a function of first order kinetics revealed Trichoderma gamsii P2-18, Aspergillus flavus JN-YG-3-5, Aspergillus niger APBSDSF96, Aspergillus fumigatus FJAT-31052, Aspergillus flavus EFB01 and Penicillium simplicissimum SNB-VECD11G have 0.47, 0.40, 0.57, 0.49, 0.41 and 0.46 rate respectively. From these findings, the growth of fungal isolates, A. fumigatus FJAT-31052 and A. flavus EFB01 were promoted and can grow in glyphosate whereas, T. gamsii P2-18 had the lowest growth promotion compared to other fungal isolates. Hence, specific growth values at the two selected points were calculated for both phases of growth and are given in Table 3 below. The data shows that the specific growth rates are comparable for the two different exponential phases. From these findings, the order of the growth of the isolates as estimated from slope of cfu growth curve are as follows: P. simplicissimum SNB-VECD11G > A.fumigatusFJAT-31052 > A. flavus EFB01 > A. niger APBSDSF96 > A. flavus JN-YG-3-5 > T. gamsii P2-18 (0.23 cfu/day, 0.2282 cfu/day, 0.2257 cfu/day, 0.2234 cfu/day, 0.2195 cfu/day and 0.2171 cfu/day) respectively. The growth of fungal isolates, A. fumigatus FJAT-31052 and A. flavus EFB01 were more promoted in glyphosate compared to others whereas, T. gamsii P2-18 had the lowest growth promotion. Therefore, we hypothesize that these isolates biodegradable ability to glyphosate will differ.
In this study, the initial pH for all the isolates were weakly acidic (within 6.0). Thereafter it declined gradually and became more acidic at the end of the experiment. The change in pH was more obvious in A. flavus EFB01 (22.06%) and lowest in A. flavusJN-YG-3-5 (19.21%). From this, we can hypothesize that fungal growth are inversely proportional with the pH. This suggest that fungal are more active in slight acidic environment compared to basic environment.
3.4 Degradation of glyphosate
The potential ability of the six fungal strains for glyphosate biodegradation were observed for 32 days (Figure 4). Our hypothesis is that these selected isolates ability to degrade glyphosate will differ because their growth in glyphosate differed. The strain T. gamsii P2-18 sp. degraded 91.45% of glyphosate leaving 930.81mg/kg of AMPA. In addition, it was observed that there was 92.07% glyphosate degradation when inoculated with A. niger APBSDSF96 leaving 113.53 mg/kg AMPA . Interestingly, A. flavusJN-YG-3-5 utilized 92.86% without accumulation of AMPA; this had the highest extent of degradation.
Overall, an analysis of the degradation efficiency of the fungi strains in glyphosate degradation showed that the isolates were efficient degraders with percentage degradation above 90% (Figure 5). However, A. flavus EFB01 had the poorest percentage degradation (27.17%) indicating poor metabolism of glyphosate. The degradation efficiency of A. flavusJN-YG-3-5 was the most efficient fungi (85.6%).
3.5 Molecular characteristics
The molecular characteristics of these promising isolates are shown in Table 5. BLAST analysis (ITS gene sequence) carried out through NCBI GenBank showed that the first two bacterial sequences were identified as strains of T. gamsii P2-18 (94.57% similarity) and A. flavus JN-YG-3-5 (99.28% similarity), respectively. Other isolates were identified as Aspergillus niger APBSDSF96 (95.22%) similarity, A. fumigatus FJAT-31052 (99.30%) similarity, A. flavus EFB01 (99.29%) similarity and P. simplicissimum SNB-VECD11G (89.91) similarity. The isolates had high level of GC contents ranging from 53.54% in P. simplicissimum SNB-VECD11G to 58.66% in Aspergillus flavus JN-YG-3-5 suggesting their potential for environmental management.
The ITS gene sequence showed that all the six isolates clustered into three group (Penicillum sp., Trichoderma sp. and Aspergillus sp.) (Figure 6) for phylogeny analyses of the isolates. Aspergillus flavus JN-YG-3-5 clustered with genus Aspergillus flavus EFB01 showing similarity, they distantly clustered with Aspergillus niger APBSDSF96 and Aspergillus fumigatus FJAT-31052. However, Trichoderma gamsii P2-18 and Penicillium simplicissimum SNB-VECD11G out clustered.
3.6 Bacteria genome annotation
Automated annotation identified several genes using a statistical significance threshold (Table 6). The genome sequences of the fungi were compared to those of several organisms (Archae generic, C. pefringes, B. subtilis and P. putida) known to function in metabolic processes. Validation of the sequence annotation using the FGENESB database yielded the following result: Rhizobium huautlense comprises 5 potential protein coding genes, 1 operon and 4 transcription units. Pseudomonas aeruginosa strain MZ4A contains 11 protein genes, 1 operon and 7 transcriptional units. Pseudomonas aeruginosa strain 22ABUH7 had 5 protein genes, 1 operon and 3 transcriptional units. Bacillus subtilis strain VBN01 had 8 protein genes, 1 operon and 5 transcriptional units. Pseudomonas aeruginosa strain HS-38 sequence was made up of 6 potential protein coding genes, 1 operon and 5 transcriptional units. Pseudomonas aeruginosa strain MZ4A and Pseudomonas aeruginosa strain HS-38 had potential protein coding genes similar to Pseudomonas putida while others did not. A search of the identified proteins for specific functions revealed that the genes are distributed in different functional categories majorly protein metabolism and respiration (Table 7). Numerous genes associated with pesticide degradation were identified.